ATLAS - Case Study
The Concept
Atlas is a conceptual AI system I designed that turns creative prompts into structured, production-ready files—not just images.
It’s built to support the actual workflows of designers, marketers, and production teams, by exporting files into Photoshop, Illustrator, and Figma with editable layers and smart segmentation.
Workflow Vision
User Flow:
Prompt the system – Describe the scene
AI generates visual + layer structure
Preview layers – View and rename layer groups
Export – PSD, SVG, or direct to Figma
Continue working in real design tools
Layer Intelligence:
Character
Background
Lighting/FX
UI or HUD
Smart Text objects
Modular branding overlays
UI Concept
I designed the Atlas interface to include:
Prompt input (left panel)
Visual preview with toggleable layers (center)
Export settings, adjustments, and tools integration (right panel)
What ATLAS Can Enable
Atlas would:
Cut visual asset production time by 50%+
Reduce localization workloads (swap text layers, not redo layouts)
Enable AI-to-human creative workflows—without breaking design systems
Make generative design usable by real teams, not just for moodboards
What I Learned
Building Atlas challenged me to think like a product owner, not just a creative lead. I had to define:
Where the AI ends and human work begins
What “usable” actually means in design workflows
How to bridge inspiration and execution
Atlas isn’t about replacing designers—it’s about engineering AI tools that respect the real work of design.
Technology Stack (Feasibility Concept)
Feature:
Visual Generation
Layer Separation
File Structuring + Export
Smart Metadata/Alt Text
Example Tech
Stable Diffusion, Firefly, DALL·E
Meta’s Segment Anything, Runway’s depth map
PSD.js, Adobe UXP SDK, Figma Plugin API
GPT-4 Vision, image captioning models
Concept By: Sarah Volynsky
Project Type: Self-Initiated Conceptual R&D
Vision: Bridge generative AI with real-world creative production by outputting fully editable, layered design files.
The Challenge
Creative teams are using AI tools like Midjourney, Runway, and Firefly to generate visuals—but once the image is generated, the process stalls. The output is just a flat JPG.
As a creative strategist, I’ve seen how much time is lost recreating editable files. Designers need layered PSDs, scalable vector files, and modular assets for localization, motion, and platform-specific needs.
Summary
Atlas is a conceptual AI product I created to explore how image generation tools could produce Photoshop- and Illustrator-ready layered files.
It’s built around how real teams work—with structure, adaptability, and speed in mind.
Concept By: Sarah Volynsky
Project Type: Self-Initiated Conceptual R&D
Vision: Bridge generative AI with real-world creative production by outputting fully editable, layered design files.
The Challenge
Creative teams are using AI tools like Midjourney, Runway, and Firefly to generate visuals—but once the image is generated, the process stalls. The output is just a flat JPG.
As a creative strategist, I’ve seen how much time is lost recreating editable files. Designers need layered PSDs, scalable vector files, and modular assets for localization, motion, and platform-specific needs.
The Concept
Atlas is a conceptual AI system I designed that turns creative prompts into structured, production-ready files—not just images.
It’s built to support the actual workflows of designers, marketers, and production teams, by exporting files into Photoshop, Illustrator, and Figma with editable layers and smart segmentation.
The Concept
Atlas is a conceptual AI system I designed that turns creative prompts into structured, production-ready files—not just images.
It’s built to support the actual workflows of designers, marketers, and production teams, by exporting files into Photoshop, Illustrator, and Figma with editable layers and smart segmentation.
Workflow Vision
User Flow:
Prompt the system – Describe the scene
AI generates visual + layer structure
Preview layers – View and rename layer groups
Export – PSD, SVG, or direct to Figma
Continue working in real design tools
Layer Intelligence:
Character
Background
Lighting/FX
UI or HUD
Smart Text objects
Modular branding overlays
UI Concept
I designed the Atlas interface to include:
Prompt input (left panel)
Visual preview with toggleable layers (center)
Export settings, adjustments, and tools integration (right panel)
Tech Stack (Feasibility Concept)
Feature:
Visual Generation
Layer Separation
File Structuring + Export
Smart Metadata/Alt Tex
Example Tech
Stable Diffusion, Firefly, DALL·E
Meta’s Segment Anything, Runway’s depth map
PSD.js, Adobe UXP SDK, Figma Plugin API
GPT-4 Vision, image captioning models
What ATLAS Can Enable
Atlas would:
Cut visual asset production time by 50%+
Reduce localization workloads (swap text layers, not redo layouts)
Enable AI-to-human creative workflows—without breaking design systems
Make generative design usable by real teams, not just for moodboards
What I Learned
Building Atlas conceptually challenged me to think like a product owner, not just a creative lead. I had to define:
Where the AI ends and human work begins
What “usable” actually means in design workflows
How to bridge inspiration and execution
Atlas isn’t about replacing designers—it’s about engineering AI tools that respect the real work of design.
Summary
Atlas is a conceptual AI product I created to explore how image generation tools could produce Photoshop- and Illustrator-ready layered files.
It’s built around how real teams work—with structure, adaptability, and speed in mind.